smoothp: smoothp
In flowfield: Forecasts future values of a univariate time series.
Description
Usage
Arguments
Value
Author(s)
References
Description
Determines the smoothing paramter in the penalized spline regression.
Usage
1
Arguments
t
Time series observation times.
y
Time series response values.
x
Design matrix from the penalized spline regression.
d
Diagonal matrix used to constrain the linear model. This is a type of Ridge regression.
Value
Returns the smoothing parameter lambda for the penalized spline regression.
Author(s)
Kyle A. Caudle
References
D. Ruppert, M. P. Wand and R. J. Carroll, Semiparametric Regression.
New York, NY: Cambidge University Press, 2003.
flowfield documentation built on May 2, 2019, 10:21 a.m.
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Description Usage Arguments Value Author(s) References
Description
Determines the smoothing paramter in the penalized spline regression.
Usage
1 |
Arguments
t |
Time series observation times. |
y |
Time series response values. |
x |
Design matrix from the penalized spline regression. |
d |
Diagonal matrix used to constrain the linear model. This is a type of Ridge regression. |
Value
Returns the smoothing parameter lambda for the penalized spline regression.
Author(s)
Kyle A. Caudle
References
D. Ruppert, M. P. Wand and R. J. Carroll, Semiparametric Regression. New York, NY: Cambidge University Press, 2003.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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